Authors :
Dr. Kavitha K S; Mamatha C G
Volume/Issue :
Volume 9 - 2024, Issue 6 - June
Google Scholar :
https://tinyurl.com/mr384ktj
Scribd :
https://tinyurl.com/65r6mrr9
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24JUN794
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Ensuring product quality and minimizing
defects is crucial in today's manufacturing industry.
Traditional manual inspections are labor-intensive and
error prone.This paper describes a system designed to
identify defects automatically the YOLOv5 algorithm,
known for its accuracy and speed. High-resolution images
of products are processed with YOLOv5 to identify
defects like scratches, dents, and deformations. This
system enhances sorting and quality assurance,
improving efficiency and consistency. Experimental
results show YOLOv5 superior performance in detection
accuracy and speed compared to traditional methods,
exploring the feasibility of combining machine learning
and image processing within manufacturing.
Keywords :
Automated Defect Detection, Image Processing, Yolov5, Quality Assurance, Manufacturing, Object Detection, Machine Learning.
References :
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Ensuring product quality and minimizing
defects is crucial in today's manufacturing industry.
Traditional manual inspections are labor-intensive and
error prone.This paper describes a system designed to
identify defects automatically the YOLOv5 algorithm,
known for its accuracy and speed. High-resolution images
of products are processed with YOLOv5 to identify
defects like scratches, dents, and deformations. This
system enhances sorting and quality assurance,
improving efficiency and consistency. Experimental
results show YOLOv5 superior performance in detection
accuracy and speed compared to traditional methods,
exploring the feasibility of combining machine learning
and image processing within manufacturing.
Keywords :
Automated Defect Detection, Image Processing, Yolov5, Quality Assurance, Manufacturing, Object Detection, Machine Learning.